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Motivated by energy saving efforts in the quartz manufacturing industry, this study investigates a single-machine rescheduling problem for a set of rework jobs arrived newly. The original jobs have release times, and the rework jobs need to be separated in a schedule in progress. The objective is to achieve energy savings by miniming the total wait...
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... Those methods provide some simple rules that are able to rank jobs and assign them to machines. Guo et al. [2021] used the shortest processing time rule (SPT) and adaptive genetic algorithm to tackle the single-machine problem to minimize the total waiting time aiming to achieve energy savings. In Zandi et al. [2020], authors investigated the problem of the parallel machine with Cmax and TEC aiming to obtain the exact Pareto frontier using a heuristic algorithm. ...
The social context in relation to energy policies, energy supply, and sustainability concerns as well as advances in more energy-efficient technologies is driving a need for a change in the manufacturing sector. The main purpose of this work is to provide a research framework for energy-efficient scheduling (EES) which is a very active research area with more than 500 papers published in the last 10 years. The reason for this interest is mostly due to the economic and environmental impact of considering energy in production scheduling. In this paper, we present a systematic literature review of recent papers in this area, provide a classification of the problems studied, and present an overview of the main aspects and methodologies considered as well as open research challenges.
... Sustainability analysis with a primary focus on the evaluation of energy consumption. Eleven articles are identified in this case that considers the exclusive study of energy consumption as a criterion for sustainability analysis [13,[27][28][29][30][31][32][33][34][35][36]. The above documents do not examine other environmental aspects or other relevant factors of a social nature, as is the particular case of occupational health and safety. ...
... Independently of the fact that in the literature reviewed [9,10,13,28,[41][42][43]45,46,52] and its theoretical support, research developments in manufacturing processes concerning the production of "non-standardized" goods using techniques based on metaheuristic methods have been widely extended since the late 1990s. It is noted that the variables associated with certain occupational hazards (high sound level, poor lighting and factors affecting the behavior of the proportion of "non-conforming" production -exposure to vibrations, weight handled and ambient temperature-) and, also, with certain economic indicators (processing time and direct personnel costs), have not been assessed simultaneously, nor have they been analyzed in the required depth: vibrations, weight handled and ambient temperature). ...
Este artículo examina algunos peligros ocupacionales específicos y ciertos indicadores económicos de sostenibilidad en un sistema de manufactura por pedido. Al respecto, se estructuran dos métodos multiobjetivo. El primero es un algoritmo genético rediseñado; el segundo está basado en sumas normalizadas. La comparación establece que el primero supera al segundo en 528%, en lo concerniente al indicador “C-Metric”.
... Yang (2007), Zhao and Tang (2010) and Liu and Zhou (2015) considered the single machine rescheduling problem when jobs have time-dependent processing times. Guo et al. (2021) studied a rescheduling problem motivated by energy savings. New orders are rework jobs that need to be added to the original sequence to minimize the total waiting time of the jobs. ...
Rescheduling problems arise in a variety of situations where a previously planned schedule needs to be adjusted to deal with unforeseen events. A common problem is the arrival of new orders, i.e. jobs, which have to be integrated into the schedule of the so-called old jobs. The maximum and total absolute time deviations of the completion times of these jobs are modeled as a disruption constraint to limit the change in the original schedule. Disruption constraints affect the shape of an optimal schedule, particularly with respect to the sequencing of old jobs and the insertion of idle time. We therefore give a classification into idle and no-idle problems for a set of single-machine rescheduling problems with different objective functions. We then prove the complexity of five rescheduling problems that have been left open in the literature.
... Moreover, [22] focused on steelmaking systems and proposed a hybrid fruit fly optimization algorithm to solve the rescheduling problem in HFSP with machine breakdowns and processing variations, while the release variation was considered in [23]. Moreover, rescheduling for a single-machine problem was studied in [24], in which the total waiting time was set as an objective and the newly arrived reworked jobs were considered. Rescheduling (in several identical parallel-machine problems) was investigated in [25]; the sequence-dependent setup times, release times, and newly arrived jobs were considered. ...
Due to the increasing level of customization and globalization of competition, rescheduling for distributed manufacturing is receiving more attention. In the meantime, environmentally friendly production is becoming a force to be reckoned with in intelligent manufacturing industries. In this paper, the energy-efficient distributed hybrid flow-shop rescheduling problem (EDHFRP) is addressed and a knowledge-based cooperative differential evolution (KCDE) algorithm is proposed to minimize the makespan of both original and newly arrived orders and total energy consumption (simultaneously). First, two heuristics were designed and used cooperatively for initialization. Next, a three-dimensional knowledge base was employed to record the information carried out by elite individuals. A novel DE with three different mutation strategies is proposed to generate the offspring. A local intensification strategy was used for further enhancement of the exploitation ability. The effects of major parameters were investigated and extensive experiments were carried out. The numerical results prove the effectiveness of each specially-designed strategy, while the comparisons with four existing algorithms demonstrate the efficiency of KCDE in solving EDHFRP.
Introducción. En el presente documento, se evalúa el comportamiento de los siguientes factores sociales y económicos de sostenibilidad: proporción “no conforme” generada por la fatiga del trabajador, nivel de intensidad del sonido, penalización del nivel de iluminación, tiempo de procesamiento (makespan) y costos directos de personal. Objetivo. En este sentido, se busca lograr la gestión equilibrada a nivel multiobjetivo de los mencionados factores de sostenibilidad, al momento de llevarse a cabo la secuenciación de un proceso de manufactura de “bienes no estandarizados”. Materiales y Métodos. Es así como, se desarrollan y comparan dos metodologías multiobjetivo. La primera hace referencia a un algoritmo híbrido; mientras que la segunda corresponde a un algoritmo fundamentado en la determinación de sumas ponderadas. Resultados. Al cotejar los valores mínimos detectados en relación con los diversos factores de interés, se encuentra que tales valores son representativamente menores, cuando se compara el “primer método” respecto al “segundo método”. Igualmente, desde la perspectiva del parámetro C-Metric, el “método híbrido” obtiene un valor que aventaja en 567 % el rendimiento del “método de sumas ponderadas”. En cuanto a lo anterior, el primer método, presenta la habilidad de hallar una alta diversidad de soluciones “no dominadas”. Conclusiones. Dado el caso que se otorgue prioridad a la implementación de tiempos de proceso pequeños, es indispensable complementar tal decisión con criterios de carácter social, buscando que se garantice la reducción de la exposición a determinados riesgos laborales. Adicionalmente, el presente estudio debe integrar a futuro conceptos propios de la dinámica de sistemas.
Rescheduling problems typically arise from production facilities that have to deal with incoming new orders for which it is not optimal to be simply scheduled at the end of an existing schedule of old jobs. A rescheduling of all jobs, old and new, is therefore allowed without disrupting too much the existing schedule. This kind of approach enables flexibility in the system while not disturbing too much the commitments with the customers. In this paper, we provide structural properties and a Branch & Memorize algorithm to solve a rescheduling problem on a single machine, where no idle times are allowed. To the authors knowledge, this is the first exact algorithm that solves a rescheduling problem with a constraint on the total absolute time-based disruption over all old jobs. The algorithm uses a fast heuristic to compute an initial upper bound and then exploits memorization techniques to cut dominated schedules. This solution method is shown to outperform an Integer Programming formulation solved by CPLEX and it is able to solve within 900 CPU seconds all instances with 10, 20, 30 jobs and most of those with 40 jobs.
In this paper, we investigate the impact of rescheduling policies in the event of both rework and reconditioning in job shop manufacturing systems. Since these events occur in unplanned and disrupting manner, to address them properly, it is required to manage real-time information and to have flexible reaction capacity. These capabilities, of data acquisition and robotics, are provided by Industry 4.0 Technologies. However, to take full advantage of those capabilities, it is imperative to have efficient decision-making processes to deliver adequate corrective actions. In this sense, we propose an event-driven rescheduling approach. This approach consists of an architecture that integrates information acquisition, optimization process, and rescheduling planning. We study the performance of the system with several algorithms with two performance criteria, namely, (i) relative performance deviation (RPD) in terms of objective function and (ii) schedule stability. We also propose a hybrid policy that combines full rescheduling regeneration with stability-oriented strategies aimed to balance both criteria. We conducted extensive computational tests with instances from the literature under different scenarios. The results show that a sophisticated algorithm can obtain better quality schedules in terms of the objective function but at the expense of sacrificing stability. Finally, we analyze and discuss the results and provide insights for its use and implementation.
